{"id":"https://openalex.org/W4380451140","doi":"https://doi.org/10.1109/taes.2023.3285201","title":"Sparse Array Design for Optimum Beamforming Using Deep Learning","display_name":"Sparse Array Design for Optimum Beamforming Using Deep Learning","publication_year":2023,"publication_date":"2023-06-13","ids":{"openalex":"https://openalex.org/W4380451140","doi":"https://doi.org/10.1109/taes.2023.3285201"},"language":"en","primary_location":{"id":"doi:10.1109/taes.2023.3285201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2023.3285201","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087650402","display_name":"Syed A. Hamza","orcid":"https://orcid.org/0000-0002-8412-7310"},"institutions":[{"id":"https://openalex.org/I138659443","display_name":"Widener University","ror":"https://ror.org/00nsyd297","country_code":"US","type":"education","lineage":["https://openalex.org/I138659443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Syed A. Hamza","raw_affiliation_strings":["School of Engineering, Widener University, Chester, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-8412-7310","affiliations":[{"raw_affiliation_string":"School of Engineering, Widener University, Chester, PA, USA","institution_ids":["https://openalex.org/I138659443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007661434","display_name":"Moeness G. Amin","orcid":"https://orcid.org/0000-0002-0926-4120"},"institutions":[{"id":"https://openalex.org/I7863295","display_name":"Villanova University","ror":"https://ror.org/02g7kd627","country_code":"US","type":"education","lineage":["https://openalex.org/I7863295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Moeness G. Amin","raw_affiliation_strings":["Center for Advanced Communications (CAC), College of Engineering, Villanova University, Villanova, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0926-4120","affiliations":[{"raw_affiliation_string":"Center for Advanced Communications (CAC), College of Engineering, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.7476,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.97765828,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"60","issue":"1","first_page":"133","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11946","display_name":"Antenna Design and Optimization","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11946","display_name":"Antenna Design and Optimization","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.723515510559082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6542956829071045},{"id":"https://openalex.org/keywords/narrowband","display_name":"Narrowband","score":0.5709128975868225},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5606377124786377},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5060965418815613},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4570922255516052},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4427066147327423},{"id":"https://openalex.org/keywords/sparse-array","display_name":"Sparse array","score":0.44134142994880676},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42725762724876404},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4254504442214966},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4159313142299652},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34382718801498413},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.14748525619506836},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11443710327148438},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09734925627708435}],"concepts":[{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.723515510559082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6542956829071045},{"id":"https://openalex.org/C2776096036","wikidata":"https://www.wikidata.org/wiki/Q1140483","display_name":"Narrowband","level":2,"score":0.5709128975868225},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5606377124786377},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5060965418815613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4570922255516052},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4427066147327423},{"id":"https://openalex.org/C145177509","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse array","level":2,"score":0.44134142994880676},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42725762724876404},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4254504442214966},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4159313142299652},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34382718801498413},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.14748525619506836},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11443710327148438},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09734925627708435},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2023.3285201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2023.3285201","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W595252221","https://openalex.org/W1514558801","https://openalex.org/W1536252645","https://openalex.org/W1981044874","https://openalex.org/W1984541135","https://openalex.org/W2003157621","https://openalex.org/W2005602327","https://openalex.org/W2009480643","https://openalex.org/W2013943064","https://openalex.org/W2028988082","https://openalex.org/W2038373830","https://openalex.org/W2079302539","https://openalex.org/W2094558966","https://openalex.org/W2098174516","https://openalex.org/W2100556411","https://openalex.org/W2110523481","https://openalex.org/W2114079824","https://openalex.org/W2124248194","https://openalex.org/W2124948632","https://openalex.org/W2131188504","https://openalex.org/W2150835235","https://openalex.org/W2153722741","https://openalex.org/W2161666352","https://openalex.org/W2169207653","https://openalex.org/W2293295048","https://openalex.org/W2316642606","https://openalex.org/W2563270628","https://openalex.org/W2616867685","https://openalex.org/W2755653495","https://openalex.org/W2762541595","https://openalex.org/W2777236243","https://openalex.org/W2919115771","https://openalex.org/W2963689780","https://openalex.org/W2971233765","https://openalex.org/W2981871664","https://openalex.org/W2987180117","https://openalex.org/W2992096220","https://openalex.org/W3002870459","https://openalex.org/W3037067838","https://openalex.org/W3128888383","https://openalex.org/W3165488499","https://openalex.org/W4237464835","https://openalex.org/W4297801963","https://openalex.org/W4297823625","https://openalex.org/W4297824792","https://openalex.org/W6631190155","https://openalex.org/W6638670064","https://openalex.org/W6683861507","https://openalex.org/W6684191040","https://openalex.org/W6714477741","https://openalex.org/W6717367658","https://openalex.org/W6729104710","https://openalex.org/W6741438122","https://openalex.org/W6779698919"],"related_works":["https://openalex.org/W19233486","https://openalex.org/W2129833531","https://openalex.org/W2117946168","https://openalex.org/W1989454727","https://openalex.org/W2051410394","https://openalex.org/W2007259720","https://openalex.org/W4385720152","https://openalex.org/W4250086616","https://openalex.org/W2028515057","https://openalex.org/W2479967241"],"abstract_inverted_index":{"This":[0],"article":[1],"considers":[2],"sparse":[3,34,94,111,138,153,172],"array":[4,112,139,154],"design":[5,19],"for":[6,50,69,183],"receive":[7],"beamforming":[8],"achieving":[9,114],"maximum":[10],"signal-to-interference":[11],"plus":[12],"noise":[13],"ratio":[14],"(MaxSINR).":[15],"We":[16,127],"develop":[17],"a":[18,106],"approach":[20],"based":[21],"on":[22],"supervised":[23],"neural":[24,75],"network":[25,53,76],"where":[26,109],"class":[27],"labels":[28],"are":[29],"generated":[30],"using":[31,60],"an":[32],"efficient":[33,184],"beamformer":[35],"spectral":[36],"analysis":[37],"(SBSA)":[38],"approach.":[39],"SBSA":[40],"uses":[41],"explicit":[42],"information":[43],"of":[44,93,125,131,136,147,150],"the":[45,52,80,84,91,110,122,129,132,137,148,151,166,170,181],"unknown":[46,81],"narrowband":[47],"interference":[48,98,157],"environment":[49],"training":[51,59],"and":[54,119,158],"bears":[55],"close":[56],"performance":[57,130],"to":[58,90,155],"exhaustive":[61],"search":[62],"by":[63,121],"enumerations":[64],"which":[65,174],"is":[66,103,116,163],"computationally":[67],"prohibitive":[68],"large":[70],"arrays.":[71],"The":[72,101],"employed":[73],"deep":[74],"(DNN)":[77],"effectively":[78,168],"approximates":[79],"mapping":[82],"from":[83],"input":[85],"received":[86],"data":[87],"spatial":[88],"correlations":[89],"output":[92,123],"configuration":[95,113,173],"with":[96],"effective":[97],"mitigation":[99],"capability.":[100],"problem":[102,108],"posed":[104],"as":[105,142,144],"classification":[107,140],"MaxSINR":[115],"one-hot":[117],"encoded,":[118],"indicated":[120],"layer":[124],"DNN.":[126],"evaluate":[128],"DNN":[133,167],"in":[134,145],"terms":[135,146],"accuracy":[141],"well":[143],"ability":[149],"classified":[152],"mitigate":[156],"maximize":[159],"signal":[160],"power.":[161],"It":[162],"shown":[164],"that":[165],"learns":[169],"optimal":[171],"has":[175],"desirable":[176],"SINR":[177],"characteristics,":[178],"hence":[179],"paving":[180],"way":[182],"real-time":[185],"implementation.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}